Pronoun mapping for sub-context rendering

ABSTRACT

An approach is provided to detect pronouns that are included in textual posts that are found in an online discussion. The textual posts are analyzed using a natural language processing speech classification technique, that results in an identification of a noun to which the detected pronoun refers. The system then displays, on a display device, the noun to which the pronoun refers.

BACKGROUND

With the increasing usage of group messaging apps, it can beincreasingly difficult for users to understand the person to which otherusers are referring. In a real-time conversation with ten users, duringwhich any number of conversations could be taking place, users withoutfull contextual understanding of the overall conversation can easilybecome confused. If these users are far enough removed from the initialsegment of the conversation, it might be impossible for such users tounderstand which users are being referred to when personal pronouns areused in the conversation.

BRIEF SUMMARY

An approach is provided to detect pronouns that are included in textualposts that are found in an online discussion. The textual posts areanalyzed using a natural language processing speech classificationtechnique, that results in an identification of a noun to which thedetected pronoun refers. The system then displays, on a display device,the noun to which the pronoun refers.

The foregoing is a summary and thus contains, by necessity,simplifications, generalizations, and omissions of detail; consequently,those skilled in the art will appreciate that the summary isillustrative only and is not intended to be in any way limiting. Otheraspects, inventive features, and advantages of the present disclosure,as defined solely by the claims, will become apparent in thenon-limiting detailed description set forth below.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The present disclosure may be better understood, and its numerousobjects, features, and advantages made apparent to those skilled in theart by referencing the accompanying drawings, wherein:

FIG. 1 depicts a schematic diagram of one illustrative embodiment of aquestion/answer creation (QA) system in a computer network;

FIG. 2 illustrates an information handling system, more particularly, aprocessor and common components, which is a simplified example of acomputer system capable of performing the computing operations describedherein;

FIG. 3 is an exemplary diagram depicting detection of pronouns intextual posts and displaying the nouns to which the pronouns refer;

FIG. 4 is an exemplary diagram depicting various processes and datastores used to perform pronoun mapping for sub-context rendering;

FIG. 5 is an exemplary high level flowchart that performs steps toprocess an online discussion for ingestion to a question answering (QA)system;

FIG. 6 is an exemplary flowchart that processes a selected post from adiscussion;

FIG. 7 is an exemplary flowchart depicting pronoun resolution of termsfound in posts of a discussion;

FIG. 8 is an exemplary flowchart depicting steps performed by theprocess that selectively ingests discussion data with resolved pronounsto a question answering (QA) system; and

FIG. 9 is a diagram showing a text viewer with resolved pronouns.

DETAILED DESCRIPTION

FIGS. 1-9 depict an approach that performs pronoun mapping forsub-context rendering. The core idea is to use natural languageprocessing and classified speech such as pronouns to generate asub-conversation. The sub-conversation includes the parent-conversationentities identified by the personal pronouns and the entities thatcreated the personal pronouns. A user interface is generated that allowsthe sub-conversation users to manage the ongoing messages relevant tothe original pronoun identified speech while allowing them to continueto be a part of the larger group conversation. The user can optionallybreak the conversation into a sub-conversation interface so that onlythe relevant responses are shown.

Example Pronouns:

SINGULAR PLURAL subjective objective possessive subjective objectivepossessive 1^(st) person I me my, mine we us our, ours 2^(nd) person youyou your, yours you you your, yours 3^(rd) person he him his they themtheir, theirs she her her, hers it it its

Traditional approaches require the users to operate in a differentcontext from the original group conversation in order to maintain arelevant conversation. Similar solutions also require that a relevantentity is explicitly called out in the original message making it timeconsuming to use and grammatically awkward.

Additional embodiments to the approach described herein include anapproach where alerts are used to notify a user of the pronoun relevantuser's response or chatting in the group conversation. In addition, theproject code name or nick name of a group or even the TV show's name canalso be used when identifying a group.

The following example is an online discussion shown with analysisperformed by the system that implements the pronoun mapping forsub-context rendering:

Nathan: “Hey everyone, you want to join us tonight?”

-   -   Identified Pronoun(s): you    -   Plurality Detected: everyone    -   Cognitive analysis: “you” referenced is referring to everyone in        chat

Ann: “I'm not sure yet—what time will you be leaving your house . . .can I ride with you?”

-   -   Identified Pronoun(s): you and your    -   Cognitive analysis: determines high confidence ranking that        pronouns are referring to the person who originated the        question, Nathan.

Sara: “I will be there! Can't wait to see the 3 of you! I'd like a ridetoo, if you have room.”

-   -   Identified Pronoun(s): you (×2)    -   Plurality Detected: 3 of (in conjunction with first use of        “you”)    -   Cognitive analysis: “3 of you” referenced is referring to other        3 participants in chat, “you” refers to Nathan, given analysis        indicates connection with previous pronoun used by Ann to want        to ride with Nathan

Rob: “Hey, yes definitely . . . Do you want me to bring anything?”

-   -   Identified Pronoun(s): you    -   Cognitive analysis: determines high confidence ranking that        pronouns are referring to the person who originated the        question/conversation, Nathan.    -   Hyperlink: “you” if clicked, Nathan's name would be shown

Nathan: “yes, if you want to bring some chips, that would be great . . .I'm going to be home til 6 pm, if you two want to ride with me”

-   -   Identified Pronoun(s): you and you two    -   Plurality Detected: two (in conjunction with second use of        “you”)    -   Cognitive analysis: determines high confidence ranking that        first you is in response to Rob's question and you two is in        response to Ann/Sara's questions

Using the above analysis, the group chat interface using the approachdescribed herein would display the conversation with references added tothe pronouns so that the reader can quickly ascertain to whom therespective pronouns are referring. In one embodiment, hyperlinks areinserted proximate to the pronouns so that the reader can click on thehyperlink next to a pronoun and receive information on exactly who thepronoun refers. In another embodiment, the actual names of theindividuals are inserted, such as in a parenthetical, next to thepronouns so that the referential pronoun names are readily seen withoutneed to click a hyperlink.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the disclosure.As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present disclosure has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the disclosure in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the disclosure. Theembodiment was chosen and described in order to best explain theprinciples of the disclosure and the practical application, and toenable others of ordinary skill in the art to understand the disclosurefor various embodiments with various modifications as are suited to theparticular use contemplated.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions. The following detailed description willgenerally follow the summary of the disclosure, as set forth above,further explaining and expanding the definitions of the various aspectsand embodiments of the disclosure as necessary.

FIG. 1 depicts a schematic diagram of one illustrative embodiment of aquestion/answer (QA) system 100 in a computer network 102. QA system 100may include knowledge manager 104, which comprises one or moreprocessors and one or more memories, and potentially any other computingdevice elements generally known in the art including buses, storagedevices, communication interfaces, and the like. Computer network 102may include other computing devices in communication with each other andwith other devices or components via one or more wired and/or wirelessdata communication links, where each communication link may comprise oneor more of wires, routers, switches, transmitters, receivers, or thelike. QA system 100 and network 102 may enable question/answer (QA)generation functionality for one or more content users. Otherembodiments may include QA system 100 interacting with components,systems, sub-systems, and/or devices other than those depicted herein.

QA system 100 may receive inputs from various sources. For example, QAsystem 100 may receive input from the network 102, a corpus ofelectronic documents 107 or other data, semantic data 108, and otherpossible sources of input. In one embodiment, some or all of the inputsto QA system 100 route through the network 102 and stored in knowledgebase 106. The various computing devices on the network 102 may includeaccess points for content creators and content users. Some of thecomputing devices may include devices for a database storing the corpusof data. The network 102 may include local network connections andremote connections in various embodiments, such that QA system 100 mayoperate in environments of any size, including local and global, e.g.,the Internet. Additionally, QA system 100 serves as a front-end systemthat can make available a variety of knowledge extracted from orrepresented in documents, network-accessible sources and/or structureddata sources. In this manner, some processes populate the knowledgemanager with the knowledge manager also including input interfaces toreceive knowledge requests and respond accordingly.

In one embodiment, a content creator creates content in a document 107for use as part of a corpus of data with QA system 100. The document 107may include any file, text, article, or source of data for use in QAsystem 100. Content users may access QA system 100 via a networkconnection or an Internet connection to the network 102, and may inputquestions to QA system 100, which QA system 100 answers according to thecontent in the corpus of data. As further described below, when aprocess evaluates a given section of a document for semantic content,the process can use a variety of conventions to query it from knowledgemanager 104. One convention is to send a well-formed question.

Semantic data 108 is content based on the relation between signifiers,such as words, phrases, signs, and symbols, and what they stand for,their denotation, or connotation. In other words, semantic data 108 iscontent that interprets an expression, such as by using Natural LanguageProcessing (NLP). In one embodiment, the process sends well-formedquestions (e.g., natural language questions, etc.) to QA system 100 andQA system 100 may interpret the question and provide a response thatincludes one or more answers to the question. In some embodiments, QAsystem 100 may provide a response to users in a ranked list of answers.

In some illustrative embodiments, QA system 100 may be the IBM Watson™QA system available from International Business Machines Corporation ofArmonk, N.Y., which is augmented with the mechanisms of the illustrativeembodiments described hereafter. The IBM Watson™ knowledge managersystem may receive an input question which it then parses to extract themajor features of the question, that in turn are then used to formulatequeries that are applied to the corpus of data. Based on the applicationof the queries to the corpus of data, a set of hypotheses, or candidateanswers to the input question, are generated by looking across thecorpus of data for portions of the corpus of data that have somepotential for containing a valuable response to the input question.

There may be hundreds or even thousands of reasoning algorithms applied,each of which performs different analysis, e.g., comparisons, andgenerates a score. For example, some reasoning algorithms may look atthe matching of terms and synonyms within the language of the inputquestion and the found portions of the corpus of data. Other reasoningalgorithms may look at temporal or spatial features in the language,while others may evaluate the source of the portion of the corpus ofdata and evaluate its veracity.

The scores obtained from the various reasoning algorithms indicate theextent to which the potential response is inferred by the input questionbased on the specific area of focus of that reasoning algorithm. Eachresulting score is then weighted against a statistical model. Thestatistical model captures how well the reasoning algorithm performed atestablishing the inference between two similar passages for a particulardomain during the training period of the QA system. The statisticalmodel may then be used to summarize a level of confidence that the QAsystem has regarding the evidence that the potential response, i.e.candidate answer, is inferred by the question. This process may berepeated for each of the candidate answers until the QA systemidentifies candidate answers that surface as being significantlystronger than others and thus, generates a final answer, or ranked setof answers, for the input question.

Types of information handling systems that can utilize QA system 100range from small handheld devices, such as handheld computer/mobiletelephone 110 to large mainframe systems, such as mainframe computer170. Examples of handheld computer 110 include personal digitalassistants (PDAs), personal entertainment devices, such as MP3 players,portable televisions, and compact disc players. Other examples ofinformation handling systems include pen, or tablet, computer 120,laptop, or notebook, computer 130, personal computer system 150, andserver 160. As shown, the various information handling systems can benetworked together using computer network 102. Types of computer network102 that can be used to interconnect the various information handlingsystems include Local Area Networks (LANs), Wireless Local Area Networks(WLANs), the Internet, the Public Switched Telephone Network (PSTN),other wireless networks, and any other network topology that can be usedto interconnect the information handling systems. Many of theinformation handling systems include nonvolatile data stores, such ashard drives and/or nonvolatile memory.

Some of the information handling systems shown in FIG. 1 depictsseparate nonvolatile data stores (server 160 utilizes nonvolatile datastore 165, and mainframe computer 170 utilizes nonvolatile data store175. The nonvolatile data store can be a component that is external tothe various information handling systems or can be internal to one ofthe information handling systems. An illustrative example of aninformation handling system showing an exemplary processor and variouscomponents commonly accessed by the processor is shown in FIG. 2.

FIG. 2 illustrates information handling system 200, more particularly, aprocessor and common components, which is a simplified example of acomputer system capable of performing the computing operations describedherein. Information handling system 200 includes one or more processors210 coupled to processor interface bus 212. Processor interface bus 212connects processors 210 to Northbridge 215, which is also known as theMemory Controller Hub (MCH). Northbridge 215 connects to system memory220 and provides a means for processor(s) 210 to access the systemmemory. Graphics controller 225 also connects to Northbridge 215. In oneembodiment, PCI Express bus 218 connects Northbridge 215 to graphicscontroller 225. Graphics controller 225 connects to display device 230,such as a computer monitor.

Northbridge 215 and Southbridge 235 connect to each other using bus 219.In one embodiment, the bus is a Direct Media Interface (DMI) bus thattransfers data at high speeds in each direction between Northbridge 215and Southbridge 235. In another embodiment, a Peripheral ComponentInterconnect (PCI) bus connects the Northbridge and the Southbridge.Southbridge 235, also known as the I/O Controller Hub (ICH) is a chipthat generally implements capabilities that operate at slower speedsthan the capabilities provided by the Northbridge. Southbridge 235typically provides various busses used to connect various components.These busses include, for example, PCI and PCI Express busses, an ISAbus, a System Management Bus (SMBus or SMB), and/or a Low Pin Count(LPC) bus. The LPC bus often connects low-bandwidth devices, such asboot ROM 296 and “legacy” I/O devices (using a “super I/O” chip). The“legacy” I/O devices (298) can include, for example, serial and parallelports, keyboard, mouse, and/or a floppy disk controller. The LPC busalso connects Southbridge 235 to Trusted Platform Module (TPM) 295.Other components often included in Southbridge 235 include a DirectMemory Access (DMA) controller, a Programmable Interrupt Controller(PIC), and a storage device controller, which connects Southbridge 235to nonvolatile storage device 285, such as a hard disk drive, using bus284.

ExpressCard 255 is a slot that connects hot-pluggable devices to theinformation handling system. ExpressCard 255 supports both PCI Expressand USB connectivity as it connects to Southbridge 235 using both theUniversal Serial Bus (USB) the PCI Express bus. Southbridge 235 includesUSB Controller 240 that provides USB connectivity to devices thatconnect to the USB. These devices include webcam (camera) 250, infrared(IR) receiver 248, keyboard and trackpad 244, and Bluetooth device 246,which provides for wireless personal area networks (PANs). USBController 240 also provides USB connectivity to other miscellaneous USBconnected devices 242, such as a mouse, removable nonvolatile storagedevice 245, modems, network cards, ISDN connectors, fax, printers, USBhubs, and many other types of USB connected devices. While removablenonvolatile storage device 245 is shown as a USB-connected device,removable nonvolatile storage device 245 could be connected using adifferent interface, such as a Firewire interface, etcetera.

Wireless Local Area Network (LAN) device 275 connects to Southbridge 235via the PCI or PCI Express bus 272. LAN device 275 typically implementsone of the IEEE 802.11 standards of over-the-air modulation techniquesthat all use the same protocol to wireless communicate betweeninformation handling system 200 and another computer system or device.Optical storage device 290 connects to Southbridge 235 using Serial ATA(SATA) bus 288. Serial ATA adapters and devices communicate over ahigh-speed serial link. The Serial ATA bus also connects Southbridge 235to other forms of storage devices, such as hard disk drives. Audiocircuitry 260, such as a sound card, connects to Southbridge 235 via bus258. Audio circuitry 260 also provides functionality such as audioline-in and optical digital audio in port 262, optical digital outputand headphone jack 264, internal speakers 266, and internal microphone268. Ethernet controller 270 connects to Southbridge 235 using a bus,such as the PCI or PCI Express bus. Ethernet controller 270 connectsinformation handling system 200 to a computer network, such as a LocalArea Network (LAN), the Internet, and other public and private computernetworks.

While FIG. 2 shows one information handling system, an informationhandling system may take many forms, some of which are shown in FIG. 1.For example, an information handling system may take the form of adesktop, server, portable, laptop, notebook, or other form factorcomputer or data processing system. In addition, an information handlingsystem may take other form factors such as a personal digital assistant(PDA), a gaming device, ATM machine, a portable telephone device, acommunication device or other devices that include a processor andmemory.

FIG. 3 is an exemplary diagram depicting detection of pronouns intextual posts and displaying the nouns to which the pronouns refer.Process 300 is an improved online discussion computer system withpronoun resolution. Users 320 are online discussion participants such asthose that contribute textual posts to an online discussion, etc. Atstep 330, the system processes incoming text received from users 320 ofthe online discussion. Step 330 includes three primary processes asshown in steps 340 through 360. At step 340, the process receives a textmessage for the online discussion from one of users 320. At step 350,the process resolves any pronouns detected in the textual post. Inaddition, pronoun resolution can occur based on references to otherparticipants in the discussion, such as someone responding to a postwith a statement such as “she really knows what she is talking about!”referring to a previous post to the online discussion. At step 360, theprocess stores the discussion data and the pronoun resolutions indiscussion tree 400. The data comprising the discussion tree is storedin data store 400.

At step 370, the process displays online discussion texts with pronounresolution assistance. For example, a pronoun may be resolved with theperson or persons to which the pronoun refers appearing in parentheticaltext or a hyperlink may be displayed referencing the pronoun that, onceselected, displays the person or persons to which the pronoun refers.Improved question-answering system 380 is shown with additionalingestion of discussion text with the pronouns found in the discussiontext being resolved as described above. At step 390, the QA system'singestion process ingests the online discussion into corpus 106 alongwith resolved pronouns of pronouns found in the discussion text.

FIG. 4 is an exemplary diagram depicting various processes and datastores used to perform inter-thread pronoun resolution. Discussion tree400 is a collection of data pertaining to an online discussion that isbeing analyzed. Post data 410 shows data elements, or attributes, thatare gathered or deduced from the various posts including the domain ofthe post, questions posed by the post, the focus of the post, anyconcepts included in the post, statements made in the post, etc. Inaddition, pronouns that are found and resolved for the post are alsostored for the post.

In discussion tree 400, post data includes a main post 420 andrelationships between posts, signified as related posts 425.Relationships include parent child relationships where one post (a childpost) is posted after and references another post (the parent post).Main post 420 serves as a parent post to one or more other (child) postsin the discussion tree.

Pronoun detection process 430 detects pronouns in identified child postsand uses referential data found in parent posts to resolve suchpronouns. Pronoun detection can be broken down into different types ofpronoun detection. These different types of pronoun detection includepronoun type 435 where a pronoun found in a child post refers to a nounfound in a parent post. For example, the pronoun “he” found in a childpost might refer to a person that was referenced in a parent post.Pronoun pronouns are stored in data store 440.

Process 475 associates the pronouns found in the child posts to theirrespective terms found in their parent posts. The resolved pronoun(e.g., the pronoun “he” resolved to a particular person's name, etc.) isstored in the post's data in data store 410. To associate pronouns toparent posts, the parent posts with the relevant terms that isreferenced by the pronoun found in the child post needs to be detected.This detection is performed by checking for referential terms indifferent types of posts.

At 480, the main post in the thread or discussion is checked forreferential terms. At 485, the parent post of the child post is checkedfor referential terms. The referential terms might not be in the main orparent post, but might be in an intervening “ancestor” post between themain post and the parent post. At 490, these ancestor posts are checkedfor referential terms. When referential terms are found in a parent post(either the main post, the immediate parent post, or an ancestor post),the relationship is noted in discussion tree 400. In addition, pronounsmight refer to participants of the online discussion. In this manner,process 475 additionally associates pronouns with one or moreparticipants of the online discussion to which the pronouns refer. Forexample, if a participant (“Sally”) posts an answer to on onlinediscussion and a subsequent post says “she is so smart, she always getsthe answer!”, then the pronoun “she” in the subsequent post isassociated to the participant (“Sally”) to which the pronoun refers.

FIG. 5 is an exemplary high level flowchart that performs steps toprocess a discussion for ingestion to a question answering (QA) system.FIG. 5 processing commences at 500 and shows the steps taken by aprocess that performs a routine that processes online discussions. Atstep 510, the process selects the first online discussion that is beingprocessed. At step 520, the process selects the first thread from theselected discussion. At step 525, the process selects the main post ofselected thread.

At predefined process 530, the main post is processed (see FIG. 6 andcorresponding text for processing details). The data gathered fromprocessing the main post is stored as post data in data store 410. Theprocess determines as to whether there are child posts to process in theselected thread (decision 540). If there are more child posts toprocess, then decision 540 branches to the ‘yes’ branch to processadditional child posts. At step 550, the process selects the next postfrom selected thread. At predefined process 560, the process performsthe process selected post routine (see FIG. 6 and corresponding text forprocessing details). The data gathered from the child post is stored aspost data in data store 410. Processing then loops back to decision 540.

Once all of the child posts are processed, decision 540 branches to the‘no’ branch whereupon the process determines as to whether there aremore threads in the selected discussion to process (decision 570). Ifthere are more threads in the selected discussion to process, thendecision 570 branches to the ‘yes’ branch which loops back to step 520to select the next thread from the selected discussion. This loopingcontinues until there are no more threads in the selected discussion toprocess, at which point decision 570 branches to the ‘no’ branch forpronoun resolution.

At predefined process 575, the process performs the pronoun resolutionroutine (see FIG. 7 and corresponding text for processing details). Thepronoun resolution routine detects pronouns found in posts from postdata store 410, resolves the pronouns with terms found in referentialdata from other posts stored in post data store 410, and resolves thepronoun by storing the identified terms referenced by the pronouns inthe post data 410.

The process determines as to whether the end of discussions beingprocessed has been reached (decision 580). If the end of discussionsbeing processed has not yet been reached, then decision 580 branches tothe ‘no’ branch which loops back to step 510 to select the nextdiscussion and process the posts in the discussion as described above.This looping continues until the end of the discussions being processedhas been reached, at which point decision 580 branches to the ‘yes’branch for further processing. At predefined process 585, the processperforms the Ingest Discussion Data with Resolved Pronouns routine (seeFIG. 8 and corresponding text for processing details). FIG. 5 processingthereafter ends at 599.

FIG. 6 is an exemplary flowchart that processes a selected post from adiscussion. FIG. 6 processing commences at 600 and shows the steps thatperform a routine that processes data found in a post. The processdetermines as to whether the post being processed is the main post ofthe discussion thread (decision 610). If the post being processed is themain post of the discussion thread, then decision 610 branches to the‘yes’ branch whereupon, at step 620, the process initializes discussiontree 400 used to store the post data associated with this discussionthread. On the other hand, if the post being processed is not the mainpost of the discussion thread, then decision 610 branches to the ‘no’branch bypassing step 620.

At step 630, the process generates a unique post identifier for thispost and adds a record used to store this post data in discussion tree400 with new post data 410. At step 640, the process identifiesreferential types based on words, terms, and phrases found in the postthat is being processed. Referential data can include the domain of thepost, questions posed by the post, the focus of the post, any conceptsincluded in the post, statements made in the post, etc. In addition,pronouns might refer to participants of the online discussion. In thismanner, at step 645, the process associates pronouns with one or moreparticipants of the online discussion to which the pronouns refer. Forexample, if a participant (“Sally”) posts an answer to on onlinediscussion and a subsequent post says “she is so smart, she always getsthe answer!”, then the pronoun “she” in the subsequent post isassociated to the participant (“Sally”) to which the pronoun refers.

At step 650, the process identifies pronoun types based on the words,terms, and phrases found in post that is being processed. Types ofpronouns include indefinite pronouns, personal-plural pronouns,personal-singular pronouns, possessive pronouns, etc.

At step 660, the process identifies any parent(s) to this post that arealready included in discussion tree 400. Parent posts include the mainpost to the thread, the direct parent post of the thread, and anyintervening parent (ancestor) posts between the main post and the directparent post. At step 670, the process adds links from this (child) postto any identified parent posts that were found in step 660. At step 675,the relationships between this post and parent posts are added to postdata included in data store 410. Links are added to this post as linksto the parent posts, and in the respective parent post data (425) aslinks to this child post with data store 425 being a subset of datastore 410 and shown as a separate data store for illustrative purposes.FIG. 6 processing thereafter returns to the calling routine (see FIG. 5)at 695.

FIG. 7 is an exemplary flowchart depicting pronoun resolution of termsfound in posts of a discussion. FIG. 7 processing commences at 700 andshows the steps taken by a process that performs a routine that resolvespronouns found in a child post. At step 710, the process selects thefirst post from discussion tree 400. At step 720, the process selectsthe first pronoun from the selected post (if an pronoun exists in thepost). At step 725, the process selects the first related post(immediate parent post, then main post, then ancestor posts) fromdiscussion tree 400. At step 730, the process selects the firstreferential term/type from the selected related post.

Table 750 depicts the relationship between pronoun types (755) and theirrespective referential types (760). Pronouns are resolved withreferential types found in a parent post of a noun or subject. At step740, the process identifies pronoun type(s) for the selected pronounbased on the referential type as shown in table 750.

The process determines as to whether the identified pronoun type(s) werefound in the selected child post (decision 765). If the identifiedpronoun type(s) were found in the selected child post, then decision 765branches to the ‘yes’ branch for continued processing. On the otherhand, if the identified pronoun type(s) were not found in the selectedchild post, then decision 765 branches to the ‘no’ branch bypassingdecision 770 and step 775. The process determines as to whether thepronoun term found in the child post matches the referential term foundin the parent post (decision 770). If the pronoun term found in thechild post matches the referential term found in the parent post, thendecision 770 branches to the ‘yes’ branch, whereupon, at step 775, theprocess annotates the pronoun relationship with related post referentialterm. In addition, at step 775, the pronoun found in the child post isresolved using the referential term found in the parent post. Theannotated pronoun relationship data and the resolved pronoun data isstored in post data 410. On the other hand, if the pronoun term found inthe child post does not match the referential term found in the parentpost, then decision 770 branches to the ‘no’ branch bypassing step 775.

The process determines as to whether there are more referential terms(pronouns) that need to be processed (decision 780). If there are morereferential terms that need to be processed, then decision 780 branchesto the ‘yes’ branch which loops back to step 730 to select and processthe next referential term. This looping continues until all referentialterms have been processed, at which point decision 780 branches to the‘no’ branch.

The process determines as to whether there are more related posts thatneed to be processed (decision 785). If there are more related poststhat need to be processed, then decision 785 branches to the ‘yes’branch which loops back to step 725 to select and process the nextrelated post. This looping continues until all related posts have beenprocessed, at which point decision 785 branches to the ‘no’ branch.

The process determines as to whether there are more pronouns included inthe selected post that need to be processed (decision 790). If there aremore pronouns included in the selected post that need to be processed,then decision 790 branches to the ‘yes’ branch whereupon processingloops back to step 720 to select and process the next pronoun from theselected post. This looping continues until all pronouns in the selectedpost have been processed, at which point decision 790 branches to the‘no’ branch.

The process determines as to whether there are more posts in thediscussion tree that need to be processed (decision 795). If there aremore posts in the discussion tree that need to be processed, thendecision 795 branches to the ‘yes’ branch which loops back to select andprocess the next post from the discussion tree. This looping continuesuntil all of the posts have been processed, at which point decision 795branches to the ‘no’ branch and processing returns to the callingroutine (see FIG. 5) at 799.

FIG. 8 is an exemplary flowchart depicting steps performed by theprocess that ingests discussion data with resolved pronouns to aquestion answering (QA) system. At step 800, the process selectivelyingests discussion posts from discussion tree 400 with resolved pronounsinto the QA System Knowledge Base (corpus) 106 with the ingestion basedon the relevance to the parent post and/or the main post. In addition,the process selectively inhibits ingestion of discussion posts withunresolved pronouns as such unresolved pronouns could lead toformulation of incorrect answers by the QA system. When requestor 810,such as a user of QA system 100, poses a question to the QA system, theQA system may provide candidate answers that utilize the ingesteddiscussion data with such ingested data including resolved pronounsfound in child post data.

FIG. 9 is a diagram showing a text viewer with resolved pronouns. Samplediscussion 900 takes place between several participants. In discussionpost 910, participant “Nathan” asks a question to all of theparticipants of the online discussion. Nathan's question “Hey everyone,you want to join me tonight?” is analyzed for pronoun references asdiscussed herein. Post data 410 keeps track of pronouns found 950, thetypes of the pronouns found 960, and the references (nouns) to which thepronoun refers. With regard to Nathan's post, the pronoun “everyone” isof type “indefinite” and refers to all of the participants of the onlinediscussion. The pronoun “you” is a personal-plural pronoun type and alsorefers to all of the participants. Finally, the pronoun “me” is apersonal-singular type of pronoun and refers to the sender of themessage, in this case “Nathan.”

In discussion post 920, participant “Ann” responds to Nathan's post witha post reading “I'm not sure yet—what time will you be leaving yourhouse . . . can I ride with you?” The pronoun “I'm” is detected as apersonal-singular pronoun and refers to the sender of this post, in thiscase Ann. Two occurrences of the pronoun “you” are detected both beingpersonal-singular pronouns and both referring to Nathan (the sender ofthe first post). The pronoun “your” is detected as a possessive pronounand refers to Nathan's house. Finally, the pronoun “I” is detected asanother personal-singular pronoun and also refers to the sender of thispost (Ann).

In discussion post 930, participant “Sara” posts: “I will be there!Can't wait to see the 3 of you! I'd like a ride too, if you have room.”The pronoun “I” is detected as a personal-singular pronoun and refers tothe sender of this post, in this case Sara. Two occurrences of thepronoun “you” are detected, however they are detected at referring todifferent nouns. The first occurrence of the pronoun “you” is detectedas a personal-plural pronoun referring to the three other participantsin the online discussion (Nathan, Ann, and Rob). The second occurrenceof the pronoun “you” is detected as a personal-singular pronoun thatrefers to Nathan (the originator of the first post).

Finally, in discussion post 940, participant “Rob” posts: “Hey, yesdefinitely . . . Do you want me to bring anything?” Here, the pronoun“you” is detected as a personal-singular pronoun referring to Nathan(the originator of the first post).

The next pronoun in Rob's post (“me”) is detected as anotherpersonal-singular pronoun that refers to Rob as the originator of thispost.

Text viewer without pronoun resolution 980 is shown with how Sara's postfrom 930 above would appear. Here, the post would appear as “I will bethere! Can't wait to see the 3 of you! I'd like a ride too, if you haveroom.” In text viewer 980, it might not be clear to whom variouspronouns refer. In contrast, text viewer with resolved pronouns 990 isshown with how the same post from 930 above appears with pronounresolution. Here the post appears as “<Sara> will be there! Can't waitto see the <Nathan, Ann, Rob>! <Sara> like a ride too, if <Nathan> haveroom.” Instead of the nouns replacing the pronouns, as shown, inalternative embodiments, hyperlinks could be used so that the nouns towhich pronouns refer are displayed when the hyperlink is selected or thepronoun and the nouns are both displayed in the viewer.

While particular embodiments of the present disclosure have been shownand described, it will be obvious to those skilled in the art that,based upon the teachings herein, that changes and modifications may bemade without departing from this disclosure and its broader aspects.Therefore, the appended claims are to encompass within their scope allsuch changes and modifications as are within the true spirit and scopeof this disclosure. Furthermore, it is to be understood that thedisclosure is solely defined by the appended claims. It will beunderstood by those with skill in the art that if a specific number ofan introduced claim element is intended, such intent will be explicitlyrecited in the claim, and in the absence of such recitation no suchlimitation is present. For non-limiting example, as an aid tounderstanding, the following appended claims contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimelements. However, the use of such phrases should not be construed toimply that the introduction of a claim element by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim element to disclosures containing only one suchelement, even when the same claim includes the introductory phrases “oneor more” or “at least one” and indefinite articles such as “a” or “an”;the same holds true for the use in the claims of definite articles.

The invention claimed is:
 1. A method implemented by an informationhandling system that includes a memory and a processor, the methodcomprising: detecting a pronoun included in one of a plurality oftextual posts included in an online discussion; analyzing the pluralityof textual posts using a natural language processing speechclassification technique, wherein the result of the analysis is anidentification of a noun to which the detected pronoun refers, andwherein the analysis further comprises: identifying, in the plurality oftextual posts, a first post comprising the noun; and selecting a set ofsecond posts, from the plurality of textual posts, that each comprisesthe detected pronoun; and displaying, on a display device, the noun towhich the pronoun refers in each of the set of second posts.
 2. Themethod of claim 1 further comprising: identifying two or moreparticipants included in the online discussion, wherein each of theparticipants is associated with a different name; and identifying thenoun based on an originator of one of the plurality of textual posts,wherein the originator is a selected one of the participants, andwherein the noun is the name associated with the selected participant.3. The method of claim 1 further comprising: generating a modifiedversion of the online discussion, wherein the modified version includesthe noun to which the detected pronoun refers; and ingesting themodified version of the online discussion into a corpus utilized by aquestion answering (QA) system.
 4. The method of claim 1 wherein thefirst post was identified based upon a participant of the onlinediscussion that created the first post and the analysis revealing thatthe detected pronoun refers to the creator of the identified first post.5. The method of claim 1 wherein the pronoun is a plural pronoun,wherein the noun to which the pronoun refers is a plurality of nouns,and wherein the method further comprises: identifying each of theplurality of nouns based on the analysis; and displaying, on the displaydevice, the plurality of nouns referenced by the detected pronoun. 6.The method of claim 5 wherein the plurality of nouns are eachparticipants included in the online discussion, and wherein the methodfurther comprises: identifying a first plurality of participantsincluded in the online discussion, wherein each of the first pluralityof participants is associated with a different name; and selecting asecond plurality of participants from the first plurality, wherein theselection is based on one or more of the second plurality ofparticipants being an originator of one of the plurality of textualposts to which the plural pronoun refers, and wherein the names of thesecond plurality of participants is included in the plurality of nouns.